{"id":6137,"date":"2011-11-01T17:59:00","date_gmt":"2011-11-01T15:59:00","guid":{"rendered":"http:\/\/hgpu.org\/?p=6137"},"modified":"2011-11-01T17:59:00","modified_gmt":"2011-11-01T15:59:00","slug":"aphog-a-framework-for-fast-object-detection-using-histograms-of-oriented-gradients","status":"publish","type":"post","link":"https:\/\/hgpu.org\/?p=6137","title":{"rendered":"APHOG: A Framework for Fast Object Detection Using Histograms of Oriented Gradients"},"content":{"rendered":"<p>In this paper we show how it is possible to improve the efficiency of existing holistic forms of object detection by refining detection areas to smaller subsets. Although this method can be applied to any form of object detection, this paper will specifically focus on the topic of pedestrian detection in lowresolution non-stationary video footage.<\/p>\n","protected":false},"excerpt":{"rendered":"<p>In this paper we show how it is possible to improve the efficiency of existing holistic forms of object detection by refining detection areas to smaller subsets. Although this method can be applied to any form of object detection, this paper will specifically focus on the topic of pedestrian detection in lowresolution non-stationary video footage.<\/p>\n","protected":false},"author":351,"featured_media":0,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"_jetpack_memberships_contains_paid_content":false,"footnotes":"","jetpack_publicize_message":"","jetpack_publicize_feature_enabled":true,"jetpack_social_post_already_shared":false,"jetpack_social_options":{"image_generator_settings":{"template":"highway","default_image_id":0,"font":"","enabled":false},"version":2}},"categories":[11,73,89,3],"tags":[1782,1791,14,20],"class_list":["post-6137","post","type-post","status-publish","format-standard","hentry","category-computer-science","category-computer-vision","category-nvidia-cuda","category-paper","tag-computer-science","tag-computer-vision","tag-cuda","tag-nvidia"],"views":2293,"jetpack_publicize_connections":[],"jetpack_featured_media_url":"","jetpack_sharing_enabled":true,"_links":{"self":[{"href":"https:\/\/hgpu.org\/index.php?rest_route=\/wp\/v2\/posts\/6137","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/hgpu.org\/index.php?rest_route=\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/hgpu.org\/index.php?rest_route=\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/hgpu.org\/index.php?rest_route=\/wp\/v2\/users\/351"}],"replies":[{"embeddable":true,"href":"https:\/\/hgpu.org\/index.php?rest_route=%2Fwp%2Fv2%2Fcomments&post=6137"}],"version-history":[{"count":0,"href":"https:\/\/hgpu.org\/index.php?rest_route=\/wp\/v2\/posts\/6137\/revisions"}],"wp:attachment":[{"href":"https:\/\/hgpu.org\/index.php?rest_route=%2Fwp%2Fv2%2Fmedia&parent=6137"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/hgpu.org\/index.php?rest_route=%2Fwp%2Fv2%2Fcategories&post=6137"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/hgpu.org\/index.php?rest_route=%2Fwp%2Fv2%2Ftags&post=6137"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}